Visualizing Better Transportation: Data & Tools

Steve Pepple

Sep 11, 2018·7 min read

The following is a collection of transportation-related data and tools for the San Francisco Bay Area and other cities in North America. These tools were originally collected and discussed at a 2018 Transit Week Event at ARUP in San Francisco.

How might we use data to create seamless travel experiences and connect San Franciscans between public transit and emerging mobility services? Starting at the Visualizing Better Transportation with Data event on Sept 26th,

Getting Started

There is a wide array of data, products, resources, and tools available and in the spirit of “emergence” and getting data out of silos, this blog post list a bunch of them. The tools, techniques, resources also make it possible to combine data in insightful ways.

Essentials

When you start working with data around transportation and geospatial analysis, you’ll enter a world full of technical terms and acronyms. It can be daunting at first, but you can learn step by step and there are countless resources to help you along the way.

Before you jump into data, here are a few essential resources and tools to take you from the basics (no coding required) to pro techniques:

• Maps 101. The Maptime meetups in San Francisco, Oakland, and other cities have a number of useful tutorials and glossaries for the world of mapping, cartography, and geospatial data.
• Building a Visualization of Transit using GTFS— A tutorial by Anya A’Hearn. Use Tableau to visualize Bart and Google’s General Transit Feed Specification data (See data below.)
• Cool Tools for Analysis of Public Transit Data— A tutorial for using Esri’s ArcGIS product to analysis transportation networks and services.
• 13 Tools and Resources for Better Data Visualizations — Article by
  Jimmy Chase
  with tools, techniques, and inspirational examples of good data visualizations.
• Getting Started with D3.js — Book includes a number of examples of using D3.js with maps and spatial analysis. One of the more interesting examples is creating a graph of the New York Metro system, which is done by analyzing the Google Transit specification for MTA with NetworkX.
• Data Science and Visualization for City Planning—
  Geoff Boeing
  ’s excellent Planetizen courses on how to model urban forms with open source and open data. Python notebooks and easy to follow code examples are here.

Transit Tools

There a number of data tools you can use to analyze and visualize transportation and geospatial data without needing to code.

• Open Street Map — Open source map of the world. If you only need data for once city like San Francisco, Interline Technologies provides bite-sized extracts of metro areas.
• Mobility Explorer — A tool for visualizing public transit networks across different modes and operators.
• Google Transit APIs — GTFS (General Transit Feed Specification) is an open data standard for public transit schedules and real-time data. (There is a similar standard for bike share.)
• Mapbox — Products and services that help you to design custom base maps and visualize data.
• Carto — Products and services for business intelligence and insights from location data. Carto allows you to quickly visualize and analyze large geospatial datasets

Transportation & Mobility Data

Now that we’ve looked at some essential tools for mapping and analyzing data, let’s look at interesting data to visualize.

The following organizations are doing exciting work in transportation and mobility. They will be showcase data and tools at our event on Sept. 26th:

• ARUP — An independent firm of designers, planners, engineers, consultants and technical specialists working across every aspect of today’s built environment. (See slides)
• SFCTA & SFMTA Emerging Mobility Committee —A joint committee between agencies that has create principles for mobility services and a number of useful tools for explorer transit and mobility in San Francisco. (See slides)
• Remix – Envision ideas, collaborate, and implement plans with a platform for the modern, multimodal city. They have a new tool for designing and visualizing scooter and bicycles. (See slides)
• Strava Metro —Plan and build better active transportation infrastructure by partnering with a global community of people on the move. (See slides)
• Swiftly — Data analytics for transit agencies for improving service quality, efficiency, and reliability. (See slides)

And here are a number of other datasets from other companies and organizations:

• 311 Dashboard — Explore 311 complaints and service request in San Francisco.
• 511.org Portal — Developer portal and open data for 511 Bay Area including data for AC Transit, BART, Caltrain, Commute.org, SFMTA, SamTrans, and other transit operators.

• Bay Area Rapid Transit APIs — BART trip planning and real-time train estimates.
• Bay Area Census — Collection of population, census, and transportation data from Metropolitan Planning Organization (MTC) and Association of Bay Area Governments (ABAG). Github projects and code are here.
• Bay Area Metro — Projects from the Metropolitan Planning Organization (MTC and ABAG) and Council of Governments.
• Congestion Explorer — An interactive map of transit and auto congestion and travel speeds.
• Data SF — More and more cities have open data portals with transportation data. The Open Data Portal for the City and County of San Francisco, for example, has regularly updated transportation datasets.
• Ford GoBike — Provides a public dataset of bicycle historical trips and real-time status. MTC bike share reports are here. (Motivate, who owns and operates Ford GoBike, also has a Developer Portal and APIs for other metro areas.)
• Jump Bikes — The Uber company has not released public data, they do have a neat blog post visualizing trips around San Francisco.

• NextBus — Provides real-time location data for a number of transportation agencies. Here is documentation on their developer API.
• SharedStreets.io — It is a data standard and a platform that serves as a launching pad for public-private collaboration and a clearinghouse for data exchange.
• San Francisco Municipal Transportation Agency (SFMTA) — Provides an interactive project map. The agency also has an open data initiative in the works to aggregate data from emerging mobility services providers.
• TNCs Today — Provides a data snapshot of Transportation Network Companies (TNCs), such as Lyft and Uber, operating in San Francisco.
• Transitland — An aggregation of transit networks maintained by transit enthusiasts and developers.
• Vital Signs Data Center — Explore a wide variety of public datasets related to transportation, land use, the economy, the environment, and social equity.

Tools & Code

Once you have the data you to want to explore and analyze, try these useful tools and libraries for analyzing and visualizing transportation and spatial data.

• D3.js — D3.js Check out all the examples in Mike Bostock’s website. For example, here is how to create a real-time transit map of San Francisco.
• Deck.gl — Open source data visualization tools from Uber. Especially good for visualization of large datasets in WebGL maps.
• Esri Transit Tools — Tools for ESRI and ArcGIS users working with transit and network data.
• Geocode.earth — Open Source geocoder (based on Mapzen’s Pelias) that allows users to look up geographic coordinates of addresses and vice versa.
  Mapbox
  ,
  CARTO
  , and Esri also have search APIs for geocoding addresses.
• Leaflet.js — the best frontend library for working with the display of points, symbols, and all types of features on the web and mobile devices. The library supports rectangles, circles, polygons, points, custom markers, and a wide variety of layers. It performs quickly, handles a variety of formats, and makes styling of map features easy.
• Opensource Routing Machine — OSRM is a project for routing paths between origin and destination in road networks. Mapbox also has a turn-by-turn Directions API and Nokia Here has a service that supports transit.
• Open source Planning Tools — An extension of GFTS for for transportation planning and network analysis.
• Replica — A city planning tool from Sidewalk labs for exploring and analyzing where people move. Here’s
  Nick Bowden
  ’s post about how the tool used de-identified or anonymous mobility and foot traffic data to model how people travel in urban areas.
• Turf.js —
  Mapbox
  library for geospatial analysis in the browser. Turf’s create collection of geographic features and then quickly spatially analyze, process, and simplify the data before visualizing it.
• UrbanSim — An open source simulation platform for supporting planning and analysis of urban development, incorporating the interactions between land use, transportation, the economy, and the environment. You can check out a simulation of the Bay Area on MTC portal.

Thanks for reading and let Transit Riders know if you have additional tools or datasets we can share. We are also looking for ideas for future events and projects. Contact us at info@sftru.org.